plot.IDEMIMP  R Documentation 
Plot imputation results
Description
Generate different types of plots for class IDEMIMP
objects generated
by imImpAll
Usage
## S3 method for class 'IDEMIMP'
plot(x, opt = c("imputed", "composite"), fname = NULL, ...)
Arguments
x 
A class IDEMIMP object returned from imImpAll

opt 
Types of the plot

fname 
File name of the result pdf file. If fname is null,
result pdf file will not be generated

... 
Options for generating the plots.
 type = imputed

deltas : Imputation sensitivity parameter for which to generate
the results
endp : If TRUE , plot the densities of the imputed
functional outcomes. Otherwise, plot the densities of the imputed
outcomes
adj density estimation option
cols plot option for colors
ltys plot options for line types
xlim plot options
ylim plot options
mfrow plot options
 type = composite

at.surv : Sets the range of the survival times to
plot in the cumulative distribution function. By default the range is the
range of survival values up to the duration of the study
at.z : Sets the range of the functional outcome to plot in the
cumulative distribution function. By defualt this is the range of the
functional outcomes plus the buffer amount to improve visibility in the
transition from survival to functional outcome
p.death : Proportion
of the plot width devoted to Survival. By default the cumulative
distribution will devote horizontal space to the survival portion that is
proportional to the number of subjects who die prior to duration
buffer : Small horizontal gap used to better visually distinguish
the transition from survival to functional outcome
delta : Imputation sensitivity parameter for which to generate the
results
seg.lab : Labels for the two components of the composite
outcome
main : plot options

See Also
imImpAll
Examples
## Not run:
im.abc < imData(abc, trt="TRT", surv="SURV", outcome=c("Y1","Y2"),
y0=NULL, endfml="Y2",
trt.label = c("UC+SBT", "SAT+SBT"),
cov=c("AGE"), duration=365, bounds=c(0,100));
rst.fit < imFitModel(im.abc);
rst.imp < imImpAll(rst.fit, deltas=c(0.25,0,0.25),
normal=TRUE, chains = 2, iter = 2000, warmup = 1000);
plot(rst.imp, opt = "imputed"),
plot(rst.imp, opt = "composite")
## End(Not run)